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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Low-Temperature Plasma-Based Metrology of Lithium-Ion Battery Electrode Materials (CRADA Final Report)

As part of the Cyclotron Road program, SirenOpt Inc. evaluated its low-temperature plasma-based metrology sensor prototype for measuring multiple critical properties of lithium-ion battery electrode materials in parallel and in real-time. Cost-effective, minimal-waste manufacturing of high-performance battery electrode materials will be vital for achieving society’s net-zero carbon emission goals. Because existing electrode metrology sensors cannot operate within most sections of manufacturing lines, manufacturers often complete hundreds of processing steps before they can test their products and detect problems. When manufacturers perform these offline tests, they typically only test a small portion of the manufactured products. Current electrode manufacturing thus often yields many low-quality products, or off-spec products that must be thrown away all together. For example, at least 6% of the total lithium-ion battery manufacturing cost (i.e., over $250 million/year for the average gigafactory) is devoted to processing defective electrodes that are not scrapped until performance tests are failed during late-stage quality control checks. Electrode variability also leads manufacturers to build extra cells into battery packs to reduce the risk of poor performance. For example, many electric vehicle (EV) manufacturers include up to 10% more cells than needed, which substantially increases the cost and weight of the final EV product. The SirenOpt sensor can potentially enable early detection of poorly manufactured electrodes and allow them to be removed earlier from manufacturing lines, which can save battery manufacturers (hundreds of) millions of dollars per year. The sensor can further be used to improve product quality by accelerating R&D and process optimization, improving quality control, and enabling real-time process control. Overall, a real-time, in-situ metrology strategy can create unprecedented opportunities for implementation of smart manufacturing practices and advanced quality and process control solutions to realize higher battery electrode throughput and performance.

25 ENERGY STORAGE↗
DOE OSTI2026

Topographic Characterization of Niobium Films on Copper for SRF Applications

Niobium films on copper substrates are being actively developed as a low-cost alternative to bulk niobium for superconducting radio-frequency (SRF) cavities, offering superior thermal conductivity, reduced material cost, and the potential for scalable cavity fabrication. The performance of such films can be limited by imperfect surfaces that reduce the peak achievable magnetic field. Nb films deposited under varied electron cyclotron resonance conditions were characterized via atomic force microscopy. The films exhibit a corrugated surface morphology which can be characterized by the depth of the corrugation, slope angle, and standard roughness parameters. The influence of this surface roughness on field limitations is examined within the framework of London theory. These measurements and models aid in understanding how ECR deposition conditions influence the nanometer-scale roughness of Nb films on Cu and its impact on high-field SRF cavity performance.

Redman, Brandi [Old Dominion Univ., Norfolk, VA (U↗
DOE OSTI2026

Producing cultivated meat cuts that match traditional meat in quality and affordability (CRADA Final Report)

Novel Farms, Inc., as a participant of the Cyclotron Road Lab-Embedded Entrepreneurship Program, investigated the performance of various animal cell lines and animal cell media formulations using its proprietary scaffolds as a growth substratum towards the development of economically-feasible cultivated meat production. As an alternative to conventionally farmed animal meat, cultivated meat production has the potential to yield a marginal carbon footprint while providing sustainable and cruelty-free animal protein. The prohibitively high cost of the growth factors necessary in animal cell culture media constitutes the primary barrier that hinders the economically viable production of cultivated meat products. Furthermore, scaffolding is required to create structured meat products, but current options are unsuitable for cost-effective large-scale production of cultivated meat. Novel Farms has developed a proprietary technology to produce scaffolding that has the potential to reduce production costs while providing an ideal 3D surface for cell growth. Developing cost-efficient methods for cultivated meat production will be vital in satisfying the growing demand for animal protein while avoiding the deforestation, carbon emissions, biodiversity loss and other negative outcomes of industrial animal farming.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Storing Electricity with Salt and Iron (CRADA Final Report)

As part of the Cyclotron Road program, Inlyte Energy, Inc. investigated low-cost energy storage for the electricity grid via batteries manufactured from abundant materials. Low-cost energy storage can solve the problem of the intermittency of wind and solar power, thereby allowing these sources of energy to scale more rapidly. The project team explored development of a Na-FeCl 2 battery—which had as its starting redox-active materials the abundant materials table salt (NaCl) and iron—that can operate safely and efficiently over a long lifetime, and be produced at very low-cost. The Na-FeCl 2 battery is architecturally similar to the commercialized Zebra (Na-NiCl 2 ) batteries, which have demonstrated safety, efficiency, and long lifetime. This project explored and assessed key design changes, including the use of planar Na-β’’-alumina solid electrolyte and lower temperatures (~200 °C) with polymer seals aimed at decreasing costs.

25 ENERGY STORAGE↗
DOE OSTI2025

Robust Polymer Electrolytes For Flexible Energy Storage (CRADA Final Report)

As part of the Cyclotron Road program, Anthro Energy investigated the formulation, synthesis, and application of advanced supramolecular compounds for lithium-ion batteries. Anthro Energy developed and tested formulations and chemistries to create polymeric materials with improved mechanical strength, safety, and electrochemical performance. These materials were explored for use in next-generation batteries with a variety of form factors. Initially, Anthro Energy tested these materials to create flexible and deformable batteries, which are in high demand for the wearable/flexible electronics industry. In future work, Anthro Energy’s materials may be applied to create rigid structural batteries, or to enable novel chemistries such as silicon anodes or lithium metal anodes. In the process of testing the company’s unique lithium-ion cells, Anthro Energy explored the development and utilization of novel cell components, cell architectures, and testing protocols. These next-generation flexible and structural batteries may eventually enable new categories of electronic devices.

25 ENERGY STORAGE↗
DOE OSTI2021

IAEA Activities on 67Cu, 186Re, 47Sc Theranostic Radionuclides and Radiopharmaceuticals

Despite interesting properties, the use of 67 Cu, 186 Re and 47 Sc theranostic radionuclides inpreclinical studies and clinical trials is curtailed by their limited availability due to a lack of widelyestablished production methods. An IAEA Coordinated Research Project (CRP) was initiated toidentify important technical issues related to the production and quality control of these emergingradionuclides and related radiopharmaceuticals, based on the request from IAEA Member States.The international team worked on targetry, separation, quality control and radiopharmaceutical aspectsof the radionuclides obtained from research reactors and cyclotrons leading to preparation ofa standard recommendations for all Member States. The CRP was initiated in 2016 with fourteenparticipants from thirteen Member States from four continents. Extraordinary results on the production,quality control and preclinical evaluation of selected radionuclides were reported in this projectthat was finalized in 2020. The outcomes, outputs and results of this project achieved by participatingMember States are described in this minireview.

Pharmacology & Pharmacy↗
DOE OSTI2022

Current State of 44 Ti/ 44 Sc Radionuclide Generator Systems and Separation Chemistry

We report in recent years, there has been an increased interest in 44Ti/44Sc generators as an onsite source of 44Sc for medical applications without needing a proximal cyclotron. The relatively short half-life (3.97 hours) and high positron branching ratio (94.3%) of 44Sc make it a viable candidate for positron emission tomography (PET) imaging. This review discusses current 44Ti/44Sc generator designs, focusing on their chemistry, drawbacks, post-elution processing, and relevant preclinical studies of the 44Sc for potential PET radiopharmaceuticals.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

The muon g-2 experiment at Fermilab

The E989 collaboration has recently published the most precise measurement of the muon anomalous magnetic moment $a_\mu$ with an uncertainty of $0.46\,\mathrm{ppm}$. The new experimental world average of $a_\mu$ deviates by 4.2 standard deviations from the Standard Model prediction provided by the Muon g-2 Theory Initiative. Emerging results from ab-initio lattice QCD calculations for hadron-physics contributions allow to scrutinize this tantalizing hint for physics beyond the Standard Model for the first time in a three way comparison. To extract the value of $a_\mu$ a frequency comparison experiment is performed with spin-polarized muons confined in a superbly controlled electric and magnetic field environment. A measurement of the difference between the Larmor and the cyclotron frequency, the so-called anomalous spin precession frequency, is combined with a high-precision measurement of the magnetic field environment which is performed using nuclear magnetic resonance techniques. I discussed the most recent result of the Fermilab Muon g-2 experiment's first physics data run performed in 2018. I reported on the experimental improvements implemented for the subsequent science runs that will allow the collaboration to achieve the ultimate goal of $0.14\,\mathrm{ppm}$ uncertainty on $a_\mu$.

Fertl, Martin↗
DOE OSTI2022

Beam dynamics corrections to the Run-1 measurement of the muon anomaly $a_{\mu}$ at Fermilab

The Fermi National Accelerator Laboratory (FNAL) Muon $g\!-\!2$ Experiment has measured the positive muon magnetic anomaly $a_{\mu} \equiv (g_{\mu}-2)/2$ with a precision of 0.46 parts per million, with data collected during its first physics run in 2018. The experimental result combined with the measurement from the former experiment at Brookhaven National Laboratory increases the tension with the Standard Model expectation to $4.2\sigma$, thus strengthening evidence for new physics.The magnetic anomaly is determined from the precision measurements of the muon spin precession frequency, relative to the muon momentum, and the average magnetic field seen by the beam. In an ideal case with muons orbiting in a horizontal plane with a uniform vertical magnetic field, the anomalous precession frequency $\omega_a$ is given by the difference between the spin ($s$) and cyclotron ($c$) frequencies, $\omega_a = \omega_s - \omega_c$. The observable $\omega_a$ is proportional to $a_{\mu}$.This proceeding presents the beam dynamics systematic corrections that are required to adjust the measured muon precession frequency $\omega^{m}_{a}$ to its true physical value $\omega_{a}$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Measurement of the muon anomalous precession frequency $\omega_a$ in the Fermilab $g-2$ experiment

The Fermilab Muon $g-2$ Experiment was designed to measure the muon's anomalous magnetic moment $a_{\mu} = (g-2)/2$ to 140 parts per billion. The value of $a_{\mu}$ is proportional to the difference frequency $\omega_a=\omega_s-\omega_c$ between the muon's cyclotron frequency and spin precession frequency in the uniform magnetic field of the $g-2$ storage ring. The frequency $\omega_a$ is extracted from the time distribution of the mu-decay positrons recorded by 24 electromagnetic calorimeters positioned around the inner circumference of the storage ring. We will discuss the various approaches to the frequency determination including the reconstruction, fitting of time distributions, and procedures for handling the effects of gain changes, positron pileup and beam dynamics. We also discuss the data consistency checks and the strategy for the averaging of $\omega_a$ across the different analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Precision Measurement of the Muon Spin Precession Frequency in the Fermilab Muon g-2 Experiment

The Fermilab Muon $g-2$ Experiment is designed to measure the muon's anomalous magnetic moment, $ a_\mu = (g-2)/2 $ with an accuracy of 140 parts per billion. This quantity is determined from two key measurements; the difference between the muon's spin precession frequency and its cyclotron frequency, given by $\omega_a = \omega_s - \omega_c$, and $\tilde{\omega_p^\prime}$, proportional to the muon-weighted magnetic field.In this talk, we focus on presenting the methodology for determining $\omega_a$. Muons with a momentum of 3.1 GeV are injected into a storage ring, and $\omega_a$ is extracted from the time distribution of decay positrons recorded by 24 electromagnetic calorimeters placed symmetrically inwards around the ring. We present the final result from the muon g-2 collaboration and analysis techniques based on data collected from 2020 to 2023.

Zaid, Estifa'a [Liverpool U.]↗
DOE OSTI2022

Microbial Communities Influence Soil Dissolved Organic Carbon Concentration by Altering Metabolite Composition

Rapid microbial growth in the early phase of plant litter decomposition is viewed as an important component of soil organic matter (SOM) formation. However, the microbial taxa and chemical substrates that correlate with carbon storage are not well resolved. The complexity of microbial communities and diverse substrate chemistries that occur in natural soils make it difficult to identify links between community membership and decomposition processes in the soil environment. To identify potential relationships between microbes, soil organic matter, and their impact on carbon storage, we used sand microcosms to control for external environmental factors such as changes in temperature and moisture as well as the variability in available carbon that exist in soil cores. Using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) on microcosm samples from early phase litter decomposition, we found that protein- and tannin-like compounds exhibited the strongest correlation to dissolved organic carbon (DOC) concentration. Proteins correlated positively with DOC concentration, while tannins correlated negatively with DOC. Through random forest, neural network, and indicator species analyses, we identified 42 bacterial and 9 fungal taxa associated with DOC concentration. The majority of bacterial taxa (26 out of 42 taxa) belonged to the phylum Proteobacteria while all fungal taxa belonged to the phylum Ascomycota. Additionally, we identified significant connections between microorganisms and protein-like compounds and found that most taxa (12/14) correlated negatively with proteins indicating that microbial consumption of proteins is likely a significant driver of DOC concentration. This research links DOC concentration with microbial production and/or decomposition of specific metabolites to improve our understanding of microbial metabolism and carbon persistence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Manhattan Project 1940s research on the prompt fission neutron spectrum

We describe how the prompt fission neutron spectrum (PFNS) was determined for the Manhattan Project at Los Alamos. Early work before World War II at American and British universities is described, together with theoretical work by Feather at Cambridge and Bethe at Los Alamos. As the Manhattan Project was being planned in 1942, two experiments on natural uranium were commissioned that proved to be influential: 1) An integral experiment at Chicago by Christy and Manley that accurately determined the average PFNS spectrum energy, 2.2 ± 0.2 MeV; 2) Bloch and Staub’s Stanford cyclotron measurement of the PFNS spectrum, which obtained an average energy of 1.70 ± 0.34 MeV. These two papers, previously unavailable outside of Los Alamos, are reproduced in the Supplementary Appendix. From these data, at the beginning of the project in 1943 Serber estimated an average 235 U PFNS energy of 2 MeV, and indeed this agrees with today’s best estimate. The challenges facing the scientists involved both the availability of only very small samples of enriched uranium and plutonium targets, and fast neutron detection technologies. During the project, 235 U and 239 Pu PFNS were measured by Nicodemus and Staub. These also proved to be quite accurate and gave an average spectrum energy of 2 MeV for 235 U. [This is not reproduced in the Appendix because it was published after the war in Physical Review 89, 1288 (1953)]. New methods were developed to enable more accurate measurements, and this paper describes how the PFNS was determined surprisingly well by 1945. We end by describing the post-war measurements in the 50s, including the PFNS data used by Ford and Wheeler in their simulations in 1951, the Bonner 1952 data, the seminal 1952 Watt paper with a new empirical parametrization of the PFNS, and the accurate PFNS measurement undertaken at Los Alamos by Cranberg et al. in 1956. We compare the measurements with our best understanding today as embodied in the Evaluated Nuclear Data File ENDF/B-VIII.0. Some images from historical documents in our Los Alamos National Security Research Center (NSRC) archives are shown.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Laser-driven production with advanced targets of Copper-64 for medical applications

Radionuclides are of paramount importance in nuclear medicine both for clinical uses and radiopharmaceutical production. Among the others, nuclides suitable for theranostics like Copper-64 are particularly attractive since they can play both a diagnostic and therapeutic role. In the last years, the growing demand for these nuclides stimulated the research of new solutions, along with cyclotrons already in use, for their production. In this respect, a promising alternative is laser-driven proton accelerators based on the interaction of superintense laser pulses with target materials. Because of their potential compactness and flexibility, they are under investigation for several applications ranging from materials science to nuclear medicine. Moreover, the use of advanced Double-Layer targets (DLTs) was identified as a viable route to increase the number and energy of the accelerated protons to satisfy the requirements of demanding applications. In this contribution, we numerically investigate the use of DLT-based laser-driven sources for Copper-64 production. We show that activities relevant to pre-clinical studies can be achieved with an existing 150 TW laser and DLTs. Moreover, we extend the discussion by considering a broad range of laser systems by exploiting a theoretical model. Our results can guide the choice of laser and target parameters for future experimental investigations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Coupled Biotic-Abiotic Processes Control Biogeochemical Cycling of Dissolved Organic Matter in the Columbia River Hyporheic Zone

A critical component of assessing the impacts of climate change on watershed ecosystems involves understanding the role that dissolved organic matter (DOM) plays in driving whole ecosystem metabolism. The hyporheic zone—a biogeochemical control point where ground water and river water mix—is characterized by high DOM turnover and microbial activity and is responsible for a large fraction of lotic respiration. Yet, the dynamic nature of this ecotone provides a challenging but important environment to parse out different DOM influences on watershed function and net carbon and nutrient fluxes. We used high-resolution Fourier-transform ion cyclotron resonance mass spectrometry to provide a detailed molecular characterization of DOM and its transformation pathways in the Columbia river watershed. Samples were collected from ground water (adjacent unconfined aquifer underlying the Hanford 300 Area), Columbia river water, and its hyporheic zone. The hyporheic zone was sampled at five locations to capture spatial heterogeneity within the hyporheic zone. Our results revealed that abiotic transformation pathways (e.g., carboxylation), potentially driven by abiotic factors such as sunlight, in both the ground water and river water are likely influencing DOM availability to the hyporheic zone, which could then be coupled with biotic processes for enhanced microbial activity. The ground water profile revealed high rates of N and S transformations via abiotic reactions. The river profile showed enhanced abiotic photodegradation of lignin-like molecules that subsequently entered the hyporheic zone as low molecular weight, more degraded compounds. While the compounds in river water were in part bio-unavailable, some were further shown to increase rates of microbial respiration. Together, river water and ground water enhance microbial activity within the hyporheic zone, regardless of river stage, as shown by elevated putative amino-acid transformations and the abundance of amino-sugar and protein-like compounds. This enhanced microbial activity is further dependent on the composition of ground water and river water inputs. Our results further suggest that abiotic controls on DOM should be incorporated into predictive modeling for understanding watershed dynamics, especially as climate variability and land use could affect light exposure and changes to ground water essential elements, both shown to impact the Columbia river hyporheic zone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Applying the core-satellite species concept: Characteristics of rare and common riverine dissolved organic matter

Introduction: Dissolved organic matter (DOM) composition varies over space and time, with a multitude of factors driving the presence or absence of each compound found in the complex DOM mixture. Compounds ubiquitously present across a wide range of river systems (hereafter termed core compounds) may differ in chemical composition and reactivity from compounds present in only a few settings (hereafter termed satellite compounds). Here, we investigated the spatial patterns in DOM molecular formulae presence (occupancy) in surface water and sediments across 97 river corridors at a continental scale using the “Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems—WHONDRS” research consortium. Methods: We used a novel data-driven approach to identify core and satellite compounds and compared their molecular properties identified with Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Results: In this work, we found that core compounds clustered around intermediate hydrogen/carbon and oxygen/carbon ratios across both sediment and surface water samples, whereas the satellite compounds varied widely in their elemental composition. Within surface water samples, core compounds were dominated by lignin-like formulae, whereas protein-like formulae dominated the core pool in sediment samples. In contrast, satellite molecular formulae were more evenly distributed between compound classes in both sediment and water molecules. Core compounds found in both sediment and water exhibited lower molecular mass, lower oxidation state, and a higher degree of aromaticity, and were inferred to be more persistent than global satellite compounds. Higher putative biochemical transformations were found in core than satellite compounds, suggesting that the core pool was more processed. Discussion: The observed differences in chemical properties of core and satellite compounds point to potential differences in their sources and contribution to DOM processing in river corridors. Overall, our work points to the potential of data-driven approaches separating rare and common compounds to reduce some of the complexity inherent in studying riverine DOM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations in previous studies, these assumptions may not be universally valid because OM degradation is a complex process governed by multiple factors. To identify key drivers of OM respiration, we performed a comprehensive analysis of diverse river systems using Fourier-transform ion cyclotron resonance mass spectrometry OM data and associated respiration measurements collected by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support of our argument, we found that the incorporation of all compounds detected in the samples into the SXTM resulted in a poor correlation between the predicted and measured respiration rates. The data-model consistency was significantly improved by the selective use of a small subset (i.e., only about 5%) of organic compounds identified using an optimization method. Through a subsequent comparative analysis of the subset of compounds (which we presume as bioavailable) against the full set of compounds, we identified three major traits that potentially determine OM bioavailability, including: (1) thermodynamic favorability of aerobic respiration, (2) the number of C atoms contained in compounds, and (2) carbon/nitrogen (C/N) ratio. We found that all three factors serve as “filters” in that the compounds with undesirable properties in any of these traits are strictly excluded from the bioavailable fraction. This work highlights the importance of accounting for the complex interplay among multiple key traits to increase the predictive power of biogeochemical and ecosystem models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗